core.md

Core & Constants

Shared constants, enums, and lightweight utilities that form the foundation of the pipeline. These modules have no heavy dependencies (no torch, spconv, pdal, numpy) and can be imported anywhere.

!!! tip "See also" Architecture: Classification Schema for the 4-class schema defined in constants.py

---

Constants

Constant	Value / Type	Description
NUM_CLASSES	4	Number of model output classes
CLASS_NAMES	dict	{0: "Background", 1: "Ground/Water", 2: "Bridge Deck", 3: "Obstacles"}
CLASS_COLORS	dict	Matplotlib colors per class (black, orange, blue, yellow)
CLASS_COLORS_HEX	dict	High-contrast hex palette for publication figures
BRIDGE_DECK_MODEL_CLASS	2	Model class for bridge deck
BRIDGE_DECK_ASPRS_CODE	17	ASPRS code for bridge deck
OBSTACLES_MODEL_CLASS	3	Model class for obstacles
OBSTACLES_ASPRS_CODE	18	ASPRS code for obstacles
VOXEL_SIZE	0.1	Default voxel size in meters
SPATIAL_SHAPE_PADDING	10	Padding added to voxel grid spatial shape
MIN_POINT_COUNT	100	Skip files with fewer points
BRIDGE_TIMEOUT	150	Default per-bridge timeout in seconds
AWS_MAX_RETRIES	3	Max S3 retry attempts (adaptive mode)

Class Mapping (ASPRS to Model)

Used at preprocessing/training time (LAS_TO_MODEL_MAP):

ASPRS Code	ASPRS Name	Model Class	Model Name
2	Ground	1	Ground/Water
9	Water	1	Ground/Water
17	Bridge Deck	2	Bridge Deck
18	High Noise	3	Obstacles
all others	-	0	Background

Used at inference time (MODEL_TO_LAS_MAP):

Model Class	Model Name	ASPRS Code	ASPRS Name
0	Background	1	Unclassified
1	Ground/Water	2	Ground
2	Bridge Deck	17	Bridge Deck
3	Obstacles	18	High Noise

::: src.constants

---

::: src.logging_utils